• 1. Introduction
  • 2. Distributed Approximating Functionals
  • 3. One-Dimensional Moment Filter
  • 3.1. Time Evolution of Moments
  • 3.2. Observation Update and Likelihood Contribution
  • 4. Exact One-Dimensional DAF-Filter
  • 5. Inference in a Bimodal Potential
  • 5.1. The Ginzburg-Landau Model
  • 5.2. Accuracy of Time Updates
  • 5.3. Maximum-Likelihood Inference
  • 6. Higher Dimensional DAF-Filter
  • 6.1. Tensorial Eigenvalue Decomposition
  • 6.2. Bivariate Diffusion example
  • 7. Stochastic Limit Cycle Model
  • 8. Conclusions
  • References